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Dell gives AI agents a broader view of enterprise data

The Unified Semantic Layer establishes a common business vocabulary across structured and unstructured data. Dell also plans to incorporate Nvidia’s open-source Auto-Ontology technology, which can help construct knowledge graphs from enterprise data. The Enterprise Knowledge Graph goes a step further by mapping relationships between data, including metadata, lineage, query history and other information. Dell says […]

The Unified Semantic Layer establishes a common business vocabulary across structured and unstructured data. Dell also plans to incorporate Nvidia’s open-source Auto-Ontology technology, which can help construct knowledge graphs from enterprise data.

The Enterprise Knowledge Graph goes a step further by mapping relationships between data, including metadata, lineage, query history and other information. Dell says this lets an AI agent identify related information across tables, data products, multimodal data and vector indexes.

The third component, Knowledge Agents, is designed to apply that context to specific business tasks. Customers can define what information an agent can access, what rules it must follow, what quality standards it must meet and how much compute or other resources it can consume. Nvidia Nemotron Retriever models will provide document retrieval, reasoning. and visual understanding capabilities for the agents.

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Stay ahead with more perspectives on cutting-edge power, infrastructure, energy,  bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

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Dell gives AI agents a broader view of enterprise data

The Unified Semantic Layer establishes a common business vocabulary across structured and unstructured data. Dell also plans to incorporate Nvidia’s open-source Auto-Ontology technology, which can help construct knowledge graphs from enterprise data. The Enterprise Knowledge Graph goes a step further by mapping relationships between data, including metadata, lineage, query history

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HPE supercharges ProLiant servers with AMD’s EPYC 9006 processors

One important attribute is that HPE iLO 8 delivers auto-SED (Self-Encrypting Drive) server capabilities, automatically protecting data at rest from the moment the server is first powered on, according to Aaron Lamond, product marketing manager, HPE Compute. “No external key manager, additional configuration, or manual activation is required. Encryption stops

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AMD to ramp up CPU, GPU supply in 2027 as AI demand surges

Faruqui noted that because Nvidia absorbs the lion’s share of TSMC’s packaging allocation for its Blackwell platforms, AMD’s ability to substantially increase its 2027 volumes therefore depends entirely on how many packaging slots it can successfully wrestle away from competitors. Lastly, while AMD is exploring broader ecosystem investments (such as

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EmbeddingGemma 2: an open, lightweight multimodal embedding model

We introduced EmbeddingGemma last year to provide a lightweight option for high-quality text embeddings, to help your apps organize, search, and connect information directly on consumer hardware. The developer community’s response blew past our expectations. With more than 20 million downloads, builders have used it to power smarter on-device search

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LNG market tightens into winter as Europe pulls US cargoes, China reopens contract talks

Global LNG markets are entering winter with limited supply cushion, even as a growing carrier fleet and shorter Atlantic voyages keep shipping rates subdued. Meanwhile China is showing signs of returning to long-term US contracting. New liquefaction capacity and higher utilization outside Qatar and the UAE have offset about 60% of Middle East LNG supply losses since March, according to a recent analysis from Morgan Stanley. Weaker demand outside Europe and European storage withdrawals have helped offset the remaining supply loss, but left inventories unusually low heading into winter. EU storage was about 70% full in late September, compared with 82% a year earlier and a 10-year average of 87%. Morgan Stanley raised its fourth-quarter JKM forecast to $27.50/MMbtu from $25/MMbtu, citing a slower Qatari restart and continued winter upside risk. Europe is drawing more flexible US supply. About 57% of US LNG exports were headed to Europe in September, up from 53% in August, while US feedgas rose about 6% month over month as Freeport recovered from an outage. Strong European demand is supporting vessel demand, but shorter US-Europe voyages and rapid fleet growth are more than offsetting that pressure. Atlantic spot rates for modern two-stroke LNG carriers stood at about $25,750/day on Oct. 6, while Pacific rates were about $39,000/day, according to Spark Commodities data. About 55 new LNG carriers were delivered in the first 7 months of 2026, with more expected by yearend. Morgan Stanley similarly noted that Asia LNG carrier rates had fallen about 80% from early-March highs and returned near pre-conflict levels, although route costs remain above levels immediately before the conflict. Meantime, the investment bank expects more than 30 million tpy of non-Middle East capacity to start by end-2027, before additional volumes from Qatar’s North Field expansion. China contracting returns China is adding another

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EIA: US crude oil inventories down 3.2 million bbl

US crude oil inventories for the week ended Oct. 2, excluding the Strategic Petroleum Reserve, decreased by 3.2 million bbl from the previous week, according to data from the US Energy Information Administration (EIA). At 424.1 million bbl, US crude oil inventories are 1% above the 5-year average for this time of year, the EIA report indicated. Gasoline inventories increased 0.4 million bbl, 6% below the 5-year average. Propane-propylene inventories decreased 1.8 million bbl, 18% above the 5-year average. Total commercial petroleum inventories decreased by 6.9 million bbl for the week. Distillate inventories remained unchanged, 12% below the 5-year average. US crude oil refinery inputs averaged 16.5 million b/d for the week ended Oct. 2, which was 223,000 b/d more than the previous week’s average. Refineries operated at 92.7% of capacity. Gasoline output averaged 9.3 million b/d, and distillate production increased to 5.3 million b/d. Crude oil imports increased 1.1 million b/d to 6.8 million b/d. The 4-week average of 6.4 million b/d is 4.3% above the year-ago level. Gasoline imports averaged 512,000 b/d; distillate imports averaged 118,000 b/d. Over the past four weeks, total product supplied averaged 21.1 million b/d, up 0.7% year over year. The 4-week average for gasoline product supplied dereased 0.3% year over year to 8.8 million b/d, while the 4-week average for distillate product supplied decreased 1.6% to 3.8 million b/d. The 4-week average for jet fuel product supplied increased 6.0% year over year.

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Chevron restructures Bakken midstream agreements, transfers Hess Midstream stake

The restructuring follows Chevron’s acquisition of Hess Corp. in July 2025. Chevron inherited Hess Corp.’s 37.8% interest in Hess Midstream, which provides midstream services to Chevron’s Bakken operations. Hess Midstream subsequently adjusted its outlook after Chevron reduced its Bakken drilling program to 3 rigs from 4 in late 2025. The lower activity led Hess Midstream to suspend its planned Capa gas plant project and lower its throughput and capital-spending expectations. Chevron is now expected to reduce its Bakken drilling program to 2 rigs in December, with Hess Midstream’s minimum revenue commitments for 2027-29 based on the 2-rig program, Hess noted. Bakken agreements Hess Midstream and Chevron will reduce the tariff rates Chevron pays for crude oil and natural gas gathering and processing services in the Bakken for 2027-33 and extend the agreements through 2045. Bakken agreements currently structured on a cost-of-service basis will convert to fixed-fee arrangements with inflation escalators. The revised agreements will include a minimum revenue commitment equal to 80% of Hess Midstream’s expected Bakken revenues attributable to Chevron through 2033. The minimum revenue commitment will be established 3 years in advance and, once established for a given year, can only increase based on updated annual development plans provided by Chevron. Minimum commitments for 2027-29 have been established on the basis of a 2-rig program, Hess Midstream said in a separate release. Hess Midstream said the revised commercial arrangements are expected to support Chevron’s investment in the Bakken. Chevron expects to sustain Bakken production through continued technology deployment and operational improvements drawn from its global shale and tight-oil portfolio. Hess Midstream expects Bakken throughput volumes to decline about 5% in 2027 as a result of reduced Chevron activity and then generally plateau beginning in 2028. DJ Basin assets Hess Midstream will acquire Chevron’s crude oil and natural gas

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DNV: Energy-importing countries scaling clean energy 3x faster than exporters

OGJ: Energy security is becoming a major driver of the energy transition. The DNV outlook found that energy-importing countries are scaling clean energy three times faster than energy-exporting countries. From the perspective of an oil and gas operator, what is the most important implication of that divergence? Alvik: I think it’s important to realize that the customers of the oil and gas business are, longer term, trying to avoid being dependent on that commodity. If you’re exporting oil like the US or Norway or Canada or Brazil or Saudi, your key strategy is to meet the shortfall of Middle East oil and gas as much as possible. But for the importer, both the vulnerability of the supply chains and the price hikes, as well as the attacks on the infrastructure, are demonstrating how vulnerable you are when you are importing any sort of critical commodity to your country, like energy is. And on top of that, you have the industry. If you have a large renewable industry, you would like that to grow. China is the best example. If you have a large oil and gas industry, you would like [that] to grow. The US is a major example of that. So, there are diverging interests leading to diverging results between importers and exporters, and this is clearer than ever. OGJ: Definitely. The Strait of Hormuz is a big part of what’s put energy security back at the center of the conversation. Do you think the current disruption represents a temporary shock to energy markets, or could it fundamentally change how governments and companies think about their exposure to imported oil and gas? Alvik: I think it could fundamentally change. The same way as the Russian attack on Ukraine dramatically changed how Germany, or Poland, or other countries were looking

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Cenovus to build oil sands business via Athabasca acquisition

“These are long-life assets located in an area where Cenovus already has a deep operating experience and strong understanding of the resource,” McKenzie said on a conference call with analysts. “They also represent one of the only remaining large-scale opportunities to add meaningful thermal reserves, resource and future development inventory within the core of the oil sands.” Among Cenovus’ growth plans is accelerating production from Athabasca’s Corner project northwest of Christina Lake by consolidating two planned expansion phases. Doing so would let Corner’s output grow to 40,000 boe/d by 2032, 3 years faster than today’s forecast. Also in the cards are efficiency projects at Athabasca’s Leismer assets that would grow production by half to about 60,000 boe/d by 2032. Michael Berger, a senior analyst at Enverus Intelligence Research, said buying Athabasca “refills Cenovus’ growth pipeline” as it relates to future production growth. The deal, he added, also “represents an escalation in oil sands deal valuations” that reflects the energy sector’s changing global dynamics. “The higher price paid by Cenovus compared to historical deals reflects a rerating of Canadian oil sands producers higher as the industry’s critical position in providing long-term oil resource in a resource-constrained world grows sharper,” Berger wrote in a commentary analyzing the acquisition plan. “While U.S. plays offer up to a decade of core inventory, the oil sands hold multiple decades. Additionally, scarcity always demands a premium and logical large-scale oil sands acquisition targets have been significantly drawn down.” The planned transaction is expected to be roughly 70% funded by cash and 30% by Cenovus shares and should close by the end of this year. It also will consolidate ownership of Duvernay Energy Corp., an oil-weighted joint venture the two companies created nearly 3 years ago that today operates more than 170 locations on roughly 90,000 net

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Energy Transfer expands Delaware basin footprint with $2.625 billion deal

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Brookfield’s AREP Deal Extends the AI Infrastructure Stack to Powered Land

The transaction goes beyond Brookfield investing in another portfolio of buildings. It is investing in a developer whose principal product increasingly begins before the building, with land, entitlements, substations, transmission access and utility capacity. PowerHouse Has Become a Gigawatt-Scale Development Platform PowerHouse was founded with a strong Northern Virginia orientation, but its development map now stretches well beyond Data Center Alley as its current portfolio includes projects in Virginia, Texas, Pennsylvania, North Carolina, Nevada, Indiana, Illinois and Kentucky. The company lists 515 MW across its Northern VA Ashburn properties, another 900 MW at its PH 95 development in Spotsylvania, 1.35 GW in Carlisle, Pennsylvania, 1.8 GW at Joliet, Illinois, and substantial campuses across multiple Texas and Indiana locations. The various projects do a good job of illustrating how the definition of a hyperscale development site is changing. At PowerHouse Arcola in Loudoun County, Virginia, PowerHouse announced a long-term hyperscale lease earlier this year. The 37-acre campus includes two planned data center buildings totaling approximately 615,000 square feet and is designed for up to 120 MW of utility capacity. PowerHouse emphasizes not only the buildings but the campus’s on-site substation, fiber access, power security and support for high-density GPU and liquid-cooled deployments. In Texas, it might be that everything really is bigger, and PowerHouse’s Grand Prairie development covers approximately 810 acres and 8.5 million developable square feet. Its project page cites maximum utility power of 1.8 GW and a development schedule extending through 2029 and beyond. The Texas development plans also include a proposed Circle T campus in Westlake outside Fort Worth, which calls for as many as four roughly 300,000-square-foot facilities totaling approximately 300 MW. According to reporting on local filings, PowerHouse has funded a 350-MW Oncor substation intended to serve the campus and the town’s pump station. The company’s development in

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AI Is Turning Energy Storage Into Active Power Infrastructure

AI Turns the Power Problem Into a Transient Problem At the heart of the issue is the changing behavior of the IT load. In a conventional data center, DeLattre said, large numbers of independent loads create a relatively predictable electrical profile. AI clusters introduce much greater synchronization. As GPUs begin processing a common workload, large numbers of accelerators can increase their power consumption simultaneously. Instead of asking the electrical infrastructure to serve a relatively smooth load, the facility can experience fast power pulses moving through the system. Hybrid supercapacitors are intended to act as a buffer between that dynamic compute load and the infrastructure supplying it. During an upward transient, storage provides some of the incremental power demanded by the IT load. When demand falls, the storage system recharges. The objective is not to create additional energy. It is to keep every upstream component — from the UPS to generators and ultimately the utility connection — from having to respond directly to every rapid change taking place inside the AI cluster. From the perspective of the upstream power source, DeLattre said, the goal is to make a highly dynamic AI load appear significantly smoother. That distinction between energy and power is central to Musashi’s argument for hybrid supercapacitors. A conventional supercapacitor, also known as an electric double-layer capacitor, can deliver very high power almost instantly but stores relatively little energy. A lithium-ion battery can store considerably more energy, but DeLattre argues that it is less suited to being aggressively charged and discharged tens or hundreds of thousands of times. Musashi’s hybrid technology uses a capacitor architecture with a lithium-doped graphite electrode intended to increase energy density while preserving the fast response and high cycling capability associated with capacitors. DeLattre reduces the distinction to a simple formulation. “Batteries are very good

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AI Infrastructure’s Next Phase: Capital, Power and the Right to Build

Capital Is Becoming Infrastructure Samsung’s $1 billion commitment to Helix Digital Infrastructure offered one of the clearest examples yet of how the capital structure surrounding AI data centers is changing. Helix was formed by KKR as an AI infrastructure platform with more than $10 billion already committed by founding investors including KKR, the Kuwait Investment Authority, NVIDIA and Vistra. Samsung’s new commitment pushes that capital base still higher. But the composition of the partnership may be more significant than another billion dollars being added to the AI infrastructure ledger. Helix is intended to invest across hyperscale data centers, power generation and transmission, fiber and other connectivity infrastructure. Samsung, meanwhile, brings capabilities extending across advanced technology, construction, energy storage and cooling. This is not simply capital chasing data center returns. It increasingly resembles an attempt to assemble the data center, energy and technology supply chain inside a single investment ecosystem. That distinction is important, because one of the defining problems of the current buildout is that capital by itself does not produce capacity. Billions of dollars can be committed long before transformers arrive, transmission is constructed, generation is secured or a campus is commissioned. The increasingly valuable infrastructure platform is therefore the one capable of controlling more of those dependencies. Lambda demonstrated another side of that evolution last week with the closing of a $1.008 billion delayed-draw term loan supporting three committed customer deployments across multiple data centers. The financing received investment-grade ratings from Morningstar DBRS and Moody’s and carries a 6.78% fixed interest rate. More importantly, it is secured by both the GPU infrastructure being financed and contracted cash flows from two investment-grade customers. Capital is drawn as infrastructure reaches commissioning milestones rather than simply being handed to Lambda upfront. That begins to make AI compute look less like speculative

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Micro data center company rolls out stackable data center for edge and AI

Stack runs on Zella Sense, a monitoring, control, and automation layer built into every Zella DC cabinet. It tracks power, cooling, servers, and suspicious activity, while monitoring things like temperature, humidity, smoke, motion, water, and doors through sensors. The system runs over SNMP, Modbus, and a full API, with email alerting and local, LDAP, RADIUS, or TACACS+ authentication. That means an edge location can be remotely monitored without requiring local staff. It also comes with access control and fire protection. Zella Stack is an indoor-only offering. Zella DC sells Zella Outback as its standalone, ruggedized outdoor micro data center, and the company says an outdoor version of Stack is planned for the second half of 2027.

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Data Center Jobs: Engineering, Construction, Commissioning, Sales, Field Service and Facility Tech Jobs Available in Major Data Center Hotspots

Each month Data Center Frontier, in partnership with Pkaza, posts some of the hottest data center career opportunities in the market. Here’s a look at some of the latest data center jobs posted on the Data Center Frontier jobs board, powered by Pkaza Critical Facilities Recruiting. Looking for Data Center Candidates? Check out Pkaza’s Active Candidate / Featured Candidate Hotlist  Lead Mechanical Engineer – Data Center DesignNew York, NY/Remote This position is also available in: Denver, CO; Indianapolis, IN; Cedar Rapids, IA; Austin, TX; White Plains, NY; Dallas, TX; Richmond, VA; Ashburn, VA; Charlotte, NC; Atlanta, GA; Phoenix, AZ; Salt Lake City, UT; Kansas City, MO; Chicago, IL; Los Angeles, CA or San Jose, CA. Our client is a leading engineering design and commissioning company that is a subject matter expert in the data center space. They will provide design coordination and construction administration, consulting and management support for the data center / mission critical facilities space with the mindset to provide reliability, energy efficiency, and sustainable design expertise when providing these consulting services for enterprise, colocation and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits. Electrical Commissioning Agent – Data Centers Austin, TX (limited travel) Non-Traveling CxA positions available in: Indianapolis, IN; Cedar Rapids, IA; Phoenix, AZ and Columbus, OH. Traveling CxA based near any major airport, otherwise traveling to: New York, NY; White Plains, NY; Dallas, TX; Richmond, VA; Montvale, NJ; Charlotte, NC; Salt Lake City, UT; Kansas City, MO; Chesterton, IN or Chicago, IL. ***Also looking for a Lead EE and ME CxA Agents and CxA PMs. *** This opportunity is with a leading EPC company of data center design / build / commissioning solutions. This company provides a complete life cycle of solutions that are custom-fit

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Startup doxx.net hands the network controls to AI

“The whole thing is run completely by AI, so behind the scenes, I mean, it’s a network with 31 locations around the world, and internally there’s a mesh network, and I can’t, as a human being, manage all of this by myself,” Lyon said. Lyon said the team modeled every site, down to the wire and the optic, in a virtual model before building. An infrastructure management system running the company’s own AI on its own hardware then ordered the installation. It orchestrated shipping and delivery through data center APIs. Human technicians performed the remote smart hands installations. The company also built tools for agents to work with users and with the network. An agent gateway gives an AI agent an identity in the doxx.net chat app. The user pastes a credential into the agent. The agent obtains its certificate and appears in the user’s chat. Users can create group chats with several agents. In one example, Lyon said one agent runs BGP while others handle other tasks.

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Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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